using the ‎nonlinear‎ kalman filter to reduce the effect of lack of measurement‏s on distribution grid state estimation

In smart distribution grids, different parameters are sent to a control center via a communication network.‏ each distribution grid state estimator uses these measurements‏. ‎the ‎state ‎estimation ‎error ‎would ‎be ‎increased if there are no measurements because of ‎the‎ communication platform is damaged or some of meters are failed. in this paper, ‎a state estimation method based on unscented kalman filter(ukf) has been proposed. the‏‏ ‎proposed‎ method is resistant to the lack of measurements for a long time.